virtual driving as an important component for functional ... · virtual driving as an important...

Virtual driving as an important component forfunctional tests of ContiGuard® Functionsfunctional tests of ContiGuard FunctionsDr.-Ing. Marc Fischer, Tobias Fiedler Continental, Kemptener Str. 99, 88131 LindauPhilipp Huth, Bernhard Schick, IPG Automotive GmbH, 76199 Karlsruhe

Agenda

1. Introduction and Motivation

2. Emergency Brake Assist “EBA City” from Continental

3 Simulation environment for “EBA City”3. Simulation environment for EBA City

4. Customer use cases and test challenges

5. Maneuver and evaluation catalogue

6. Benefits and Conclusion

IPG Automotive GmbH Conference Safety through Driver Assistance 2010, Munich Sheet 2

Introduction and Motivation

Our Vision: Zero Accidents

This Requires Safety Solutions for all Price Segments and Situations

One part of the Puzzle is the Emergency Brake Assist (EBA) City

Target is to reduce accidents in the Speed Range below 30 km/h

Bitte Absenderangaben auf dem Folienmaster ändern ein- oder zweizeilig)

3 / Dr.-Ing. Marc Fischer / Datum © Continental AG

Introduction and Motivation

69% of accidents with injuries to persons are in city areas up to 30 kph

228717221306

2007 2008

Source: Statistisches Bundesamt

86662

20466

81039

18269

In City Out of City Autobahn

Casualties with injury to persons in Germany

Rear collision is the most frequent collusion type

Main reason is the lack of attention of the driver

“Emergency Brake Assist” from Continental was developed to support drivers in these situations


Closing Velocity Sensor – Sensor Platform for EBA City

Principle of CV - Closing Velocity Sensor for environment identification

Sensor Principle: Time of Flight of Light PulsesWave length: IRMounting Position: behind WindscreenMounting Position: behind Windscreen

at interior rear view mirror

• Sensor generates 3 independent Beamsg p• Operation Range up to approx. 10 m


EBA City – 3 FunctionalitiesEBA City

PreFill

Preconditioning ofthe Brake System

ObstacleObstacle




PreFill ppBrake AssistSupport


Sensitivity Adjustmentof Brake AssistThresholds

ObstacleObstacle




PreFill ppBrake AssistSupport g

AutonomousBraking


Sensitivity Adjustmentof Brake AssistThresholds

Graded,AutonomousDecelerationRequestRequest

ObstacleObstacle



Challenges for the Development

Development of a complex System

(multiple components, Sensor, Brake System etc.)( p p , , y )

Driver Assistant function with strong intervention into vehicle dynamics

Functionality has to consider physical behavior of vehicle

consideration of complex driving scenarios

(e.g. evasion by steering, etc.)



Requirements for a Simulation Tool

Closed Loop Simulation

Multiple domain Simulation (sensoric, brake systems, vehicle dynamics)

Possibility to perform rapid testing of algorithmsPossibility to perform rapid testing of algorithms

Realistic and adaptable vehicle models

Simulate complex scenarios driver model + maneuver control

Realistic brake hydraulic modely

Real time capability for HIL

I t f b t i l t d i t d d lInterface between simulated environment and sensor model



Simulation environment for “EBA City”

CarMaker simulation platform was used for vehicle – driver – road – traffic

Field of applications for ADAS (samples)

driverdrivervehiclevehicleclosed loop

Parking AssistanceAdapti e Cr ise Control Parking AssistanceAdaptive Cruise Control

roadroadtraffictraffic

IPG Automotive GmbH 11

Lane Keeping AssistanceCollision Avoidance


Real system

Vi t l i t

CV-Sensor CV Sensor with EBA CityTest vehicle

Virtual environment

12IPG Automotive GmbH Sheet 12Final presentation of the Bachelor’s thesis, 12.10.2009

DA Sensor Model SIMULINK ModelVehicle Dynamics Model


Brake SystemDeceleration

Request EnEnSensor ECUSensor ECU Real World

Key models have been integrated into CarMaker model platform

Vehicle Datae.g. Speed, Yaw Rate, Long. Acceleration etc.

nvironment

nvironment

SensoricsSensoricsFunction

on Target HW

Functionon

Target HW

relevantObject

g

DecelerationRequest

3D3D

relevantObject

ECUECU SS

ObjectList

Brake Model 3D Enviro3D Enviro

SensorMaskModel

SensorMaskModel

Simulation

MeasurementError Measurement

E

ECUFunctionSIMULINK

ECUFunctionSIMULINK

SensorBehavioral

Model

SensorBehavioral

Model

Vehicle Dynamics Model

Vehicle Data

onment Mode

onment ModeContinental

Errorall Objects with ideal properties within

detection range


Vehicle Dynamics Model elel

CarMakerContinental

A vehicle control module allow the interaction of driver and ADASA vehicle control module allow the interaction of driver and ADAS


systems

rr trol

trol

del

del

ring

rtrain

ynam

icee

l rie

r elel del

del

PGD

river

PGD

river

Driv

Man

Driv

Man

cle

Con

tcl

e C

ont

icle

Mod

icle

Mod St

eer

Tire

Mod

elTi

re M

odel

sion

Powe

re

Aero

dy cor

Whe

carr

y

Driving Tasks Vehicle Reaction

oad

Mod

eoa

d M

ode

affic

Mod

affic

Mod

IPIP DD

Vehi

Vehi

Veh

Veh TT

Susp

ens

Brak

e

Sens

o

Body

Ro

Ro

Tra

Tra

CLOSED LOOP

Driver model is embedded in a drive maneuver control moduleDriving tasks management and event driven operationsMonitoring and analysis of all quantitiesMonitoring and analysis of all quantities

HMI for drivers wish + vehicle control interface for cooperative functionsSteering wheel, pedal (brake, accel., clutch), shift, cockpit switches etc.


Acc/Dec interface and steer angle /torque interface for system requests


Following approaches and boundary conditions have been considered

Simulation provide first of all ideal object information e.g. position, size, speed, acceleration are exactly knownFor comparability with real test scenarios - at least partial sensor properties (measurement errors) must be modeledQuality of vehicle information on CAN (e.g. speed) suffers fromQuality of vehicle information on CAN (e.g. speed) suffers from measurement errors (absolute, temporary, delay’s, noise etc.). This could lead to difference to real testing. A systematic signal manipulation within the test maneuver must be possible


y g p pto investigate the failure robustness

Customer use cases and test challenges

Simulation shall reconstruct real use cases by event triggered maneuvers

Pure longitudinal mission

speed difference to moving or stationary objects (e.g. drive against obstacle)

Pure lateral mission

lateral moving object (e.g. vehicle sheer in)

avoiding obstacle (e.g. speed breaks and chicanes in play streets)

Combined longitudinal and lateral mission

lateral moving object with speed difference (e.g. vehicle sheer in)

IPG Automotive GmbH 16

lateral moving object with speed difference (e.g. vehicle sheer in)

avoiding moving obstacle with speed difference (e.g. entrance at parking area)


Event triggered maneuvers guarantee reproducibility and reusability

Obstacle avoidanceObstacle avoidanceReal test driving Real test driving

Obstacle avoidanceObstacle avoidanceVirtual test driving Virtual test driving

How probable is the collision situation?

How easy is the avoidance by steer? d steer intervention


d steer intervention


Event triggered maneuvers by monitor and analyze of related quantities

Sample 1: Pure longitudinal maneuversMan 2: ConstantMan 2: ConstantMan 2: ConstantMan 2: Constant Man 3: AccelerationMan 3: AccelerationMan 3: AccelerationMan 3: Acceleration Man 2: BrakingMan 2: BrakingMan 2: BrakingMan 2: Braking Man 1Man 1Man 1Man 1

d trigger

Sample 2: Pure lateral maneuversMan 1: AccelerationMan 1: AccelerationMan 1: AccelerationMan 1: Acceleration Man 2: Constant DrivingMan 2: Constant DrivingMan 2: Constant DrivingMan 2: Constant Driving Man 1: ConstMan 1: ConstMan 1: ConstMan 1: Const


Man 3: Lane OffsetMan 3: Lane OffsetMan 3: Lane OffsetMan 3: Lane Offset



Sample 3: Combined longitudinal and lateral maneuvers

Maneuver and evaluation catalogue

Functional Safety Assessment E t T A l i

A detail maneuver test catalogue have been developed based on …

Event Tree AnalysisReal Test ProceduresField Experience

Maneuvers Description Maneuver parameters Evaluation Criteria'sVariations



For each maneuver test variations and default values have been defined

Maneuver 6: Obstacle Avoidance Maneuver 9: Alleyway driving

TTC maneuver start

TTC maneuver start

Test Variation Test Variation Vehicle speed Obstacles speed Obstacles offset

Vehicle velocityObstacle velocityAlleyway widthObstacles offset

Obstacles initial s-road Driver steer angel / speedDriver gas

Alleyway widthcurvature / curve radiusAccelerator positionDecelerator position


Driver gasTTC maneuver start

Decelerator position


For each maneuver evaluation criteria’s have been created and allocated

Maneuver 6: Obstacle Avoidance Maneuver 9: Alleyway driving

Characteristic Valuesds_min [m]Car.ax_max [m/s²]Prefill [0,1]AutoBraking [0 1]

ds_AutoBraking [m]dec.t [s]relspeed [m/s]TTC avoid manstart [s]AutoBraking [0,1]

TTC [s]Impact [0,1]Driver.Brake [%]

TTC.avoid_manstart [s]Alley_width [m]Reaction [s]Reaction_losingdist [m]

Prefill

AutoBraking


Driver.Gas [%]ds_Prefill [m]

Impact.v [m/s]Impact.Angl [°]

AutoBraking


A test management tool was applied with maneuver and evaluation catalogue

Vehicle Configuration• Handover key values e.g. engine, tire …

Test Group Definition• e.g. longitudinal, lateral maneuvers … Qualification

Test Case 1• Test Case selection e.g. TestRun

Parameter VariationParameter Variation

Parameter Variations• Variation list of any system parameter• vehicle, road, controller,

test execution etc of all InfoFiles!

Test Case 2• Test Case selection e.g. TestRun


CONCERTO Application• Automatic start of post-processing

Benefits and Conclusion

Successful Closed Loop simulation of ADAS function with environment sensor

Implementation of a TestManager with respects to the demands from ADAS functions p g p

Benefits utilizing simulation for the development of ADAS functions:

Simulation studies for “Functional Safety Assessment” y

In the Loop Algorithm tests in the development phase

Parameter studies for integrated functions and related valid rangesg g

Virtual testing of functional system behavior

Test of “Failure Resistance” by failure imprint (maneuver driven)


y p ( )

Virtual pre-tests for test matrix reduction of road tests

Thank YouThank You

Virtual driving as an important component forfunctional tests of ContiGuard® Functionsfunctional tests of ContiGuard FunctionsDr.-Ing. Marc Fischer, Tobias Fiedler Continental, Kemptener Str. 99, 88131 LindauPhilipp Huth, Bernhard Schick, IPG Automotive GmbH, 76199 Karlsruhe

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